Triple
T8524760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Distinguished Service Cross (United States) |
E201783
|
entity |
| Predicate | mayBeAwardedToForeignMilitary |
P83147
|
FINISHED |
| Object | true |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: true | Statement: [Distinguished Service Cross (United States), mayBeAwardedToForeignMilitary, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayBeAwardedToForeignMilitary Context triple: [Distinguished Service Cross (United States), mayBeAwardedToForeignMilitary, true]
-
A.
canBeAwardedInWartime
Indicates that the associated honor, status, or recognition is eligible to be granted during periods of armed conflict or war.
-
B.
isMilitaryAwardFor
Indicates that something is a military honor or decoration given in recognition of a specific action, service, or achievement.
-
C.
countryOfMilitaryService
Indicates that an entity served or is serving in the armed forces of a specified country.
-
D.
hasMilitaryAssociation
Indicates a relationship in which an entity is connected or affiliated with a military organization, activity, or function.
-
E.
isCivilianAward
Indicates that an award is designated for civilians rather than military or combat-related recipients.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca83228b24819085d22e7dc99f5d94 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe644c4648190a14dcaeaa90d72c7 |
completed | March 31, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69cbd10f64b4819080859057c19e58f0 |
completed | March 31, 2026, 1:50 p.m. |
| PDg | Predicate description generation | batch_69cbe30d453481908f897ed2b06e7534 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:16 p.m.